• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.1
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• pp.41-53
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• 2016

Static repositioning is a well-known and commonly used strategy to maximize customer satisfaction in public bike-sharing systems. Repositioning is performed by trucks at night when no customers are in the system. In models that represent the static repositioning problem, the decision variables are truck routes and the number of bikes to pick up and deliver at each rental station. To simplify the problem, the decision on the number of bikes to pick up and deliver is implicitly included in the truck routes. Two relocation-based local search algorithms (1-relocate and 2-relocate) with the best-accept strategy are incorporated into a variable neighborhood search (VNS) to obtain high-quality solutions for the problem. The performances of the VNS algorithm with the effect of local search algorithms and shaking strength are evaluated with data on Tashu public bike-sharing system operating in Daejeon, Korea. Experiments show that VNS based on the sequential execution of two local search algorithms generates good, reliable solutions.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.3
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• pp.1-9
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• 2007

A major concern for Autonomous Military Robot in the rough terrain is the problem of moving robot from an initial configuration to goal configuration. In this paper, We generate a local path to looking for the best route to move an goal configuration while avoiding known obstacle from world model, not violating the mobility constraints of robot. Trough a Simulator for Unmanned Autonomous Vehicle, We can simulate a traversability of unmanned autonomous vehicle based on steering, acceleration, braking command obtained from local path planning.

• KIEE International Transactions on Power Engineering
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• v.5A no.2
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• pp.177-185
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• 2005

This paper proposes an expert system that can enhance the accuracy of real-time bus reconfiguration strategy by adopting the local minimum tree search method and that can minimize the spreading effect of the fault by considering the operating condition when a main transformer fault occurs in an automated substation. The local minimum tree search method is used to expand the best-first search method. This method has the advantage that it can improve the solution performance within the limits of the real-time condition. The inference strategy proposed expert system consists of two stages. The first stage determines the switching candidate set by searching possible switching candidates starting from the main transformer or busbar related to the event. The second stage determines the rational real-time bus reconfiguration strategy based on heuristic rules from the obtained switching candidate set. Also, this paper proposes generalized distribution substation modeling using graph theory, and a substation database based on the study results is designed.

• Proceedings of the KOR-KST Conference
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• 2000.02a
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• pp.89-115
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• 2000

Traffic signal setting policies and traffic assignment procedures are mutually dependent. The combined signal control and traffic assignment problem deals with this interaction. With the total travel time minimization objective, gradient based local search methods are implemented. Deterministic user equilibrium is the selected user route choice rule, Webster's delay curve is the link performance function, and green time per cycle ratios are decision variables. Three implemented solution codes resulting in six variations include intersections operating under multiphase operation with overlapping traffic movements. For reference, the iterative approach is also coded and all codes are tested in four example networks at five demand levels. The results show the numerical gradient estimation procedure performs best although the simplified local searches show reducing the large network computational burden. Demand level as well as network size affects the relative performance of the local and iterative approaches. As demand level becomes higher, (1) in the small network, the local search tends to outperform the iterative search and (2) in the large network, vice versa.

• Korean System Dynamics Review
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• v.12 no.2
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• pp.127-151
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• 2011

The purpose of this study is to examine measures to improve government's supply oriented housing policy in population declining cities. For this purpose, system dynamics simulation method was used to build urban-housing model and different sets of housing policies were tested to see their impact on local housing problems. Simulation result shows that there is no best set of housing policies that can solve all housing problems in population declining cities. It also indicates that housing policy that solve one type of problems can worsen other type of problems. Housing policy that increases population size has negative effect of housing oversupply. It also increases proportion of old houses in population declining cities. However, housing policy that makes city younger with newer houses tends to increase housing shortage and housing price. So, policy choice needs to be made with clear understanding of trade off between different policies. The result also shows it is difficult to expect a full scale effect of housing policy on local housing problems unless it is executed with regional economic development policy because local housing problems are so closely related with local economic problem in population declining local cities.

• Structural Engineering and Mechanics
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• v.67 no.4
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• pp.417-425
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• 2018

The main aim of this paper is to investigate the bending of Euler-Bernouilli nano-beams made of bi-directional functionally graded materials (BDFGMs) using Eringen's non-local elasticity theory in the integral form with compare the differential form. To the best of the researchers' knowledge, in the literature, there is no study carried out into integral form of Eringen's non-local elasticity theory for bending analysis of BDFGM Euler-Bernoulli nano-beams with arbitrary functions. Material properties of nano-beam are assumed to change along the thickness and length directions according to arbitrary function. The approximate analytical solutions to the bending analysis of the BDFG nano-beam are derived by using the Rayleigh-Ritz method. The differential form of Eringen's non-local elasticity theory reveals with increasing size effect parameter, the flexibility of the nano-beam decreases, that this is unreasonable. This problem has been resolved in the integral form of the Eringen's model. For all boundary conditions, it is clearly seen that the integral form of Eringen's model predicts the softening effect of the non-local parameter as expected. Finally, the effects of changes of some important parameters such as material length scale, BDFG index on the values of deflection of nano-beam are studied.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.373-378
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• 2003

This study deals with development of transformation tool for transformation of digital map coordinates systems using by the best fit transformation parameters which are determined between the local geodetic datum and geocentric datum (ITRF2000) in Korea and distortion modelling derived from collocation method. We used 107 control points as a common points. For analyzing the derived parameters, another 83 common points are tested. Finally, the best fit parameters are determined from Molodensky-Badekas model after considering the RMSE, maximum value, minimum values, and 95% confidence interval of residuals. after transformation of best fit parameters and distortion modelling, we could develop transformation tools with advenced accuracy. so it is possible to perform on transformation of digital map with scale 1:5,000. and we tested accuracy eveluation through analysis between transformation results and field results of GPS observation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.166-169
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• 2003

Reinforcement learning if a kind of machine learning. It aims to adapt an agent to a given environment with a clue to a reward and a penalty. Q-learning [8] that is a representative reinforcement learning system treats a reward and a penalty at the same time. There is a problem how to decide an appropriate reward and penalty values. We know the Penalty Avoiding Rational Policy Making algorithm (PARP) [4] and the Penalty Avoiding Profit Sharing (PAPS) [2] as reinforcement learning systems to treat a reward and a penalty independently. though PAPS is a descendant algorithm of PARP, both PARP and PAPS tend to learn a local optimal policy. To overcome it, ion this paper, we propose the Multi Best method (MB) that is PAPS with the multi-start method[5]. MB selects the best policy in several policies that are learned by PAPS agents. By applying PS, PAPS and MB to a soccer game environment based on the SoccerBots[9], we show that MB is the best solution for the soccer game environment.

• Radiation Oncology Journal
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• v.34 no.2
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• pp.113-120
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• 2016

Purpose: The association between metabolism and cancer has been recently emphasized. This study aimed to find the prognostic significance of obesity in advanced stage rectal cancer patients treated with surgery and radiotherapy (RT). Materials and Methods: We retrospectively reviewed the medical records of 111 patients who were treated with combined surgery and RT for clinical stage 2-3 (T3 or N+) rectal cancer between 2008 and 2014. The prognostic significance of obesity (body mass index [BMI] ${\geq}25kg/m^2$) in local control was evaluated. Results: The median follow-up was 31.2 months (range, 4.1 to 85.7 months). Twenty-five patients (22.5%) were classified as obese. Treatment failure occurred in 33 patients (29.7%), including local failures in 13 patients (11.7%), regional lymph node failures in 5, and distant metastases in 24. The 3-year local control, recurrence-free survival, and overall survival rates were 88.7%, 73.6%, and 87.7%, respectively. Obesity (n = 25) significantly reduced the local control rate (p = 0.045; 3-year local control, 76.2%), especially in women (n = 37, p = 0.021). Segregation of local control was best achieved by BMI of $25.6kg/m^2$ as a cutoff value. Conclusion: Obese rectal cancer patients showed poor local control after combined surgery and RT. More effective local treatment strategies for obese patients are warranted.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.587-598
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• 2006

The number of variables exceeds the number of samples in microarray data. We propose a nonparametric local linear logistic classification procedure using orthogonal components for classifying high-dimensional microarray data. The proposed method is based on the local likelihood and can be applied to multi-class classification. We applied the local linear logistic classification method using PCA, PLS, and factor analysis components as new features to Leukemia data and colon data, and compare the performance of the proposed method with the conventional statistical classification procedures. The proposed method outperforms the conventional ones for each component, and PLS has shown best performance when it is embedded in the proposed method among the three orthogonal components.